Empowering enterprises to operate at the speed of insight!
Toronto, Ontario
AI systems for how organizations actually operate. Our intelligent solutions power real-time decisions across the enterprises and institutions that modern economies depend on. At ShyftLabs, we build platforms designed for trusted enterprise deployment, with governed data infrastructure, privacy-first architecture, secure integrations, and responsible AI controls at the core. With experts across Toronto, New York, Dubai, and New Delhi, we turn vision into actual impact.
Hybrid · Toronto
The Program Manager will establish and manage operational governance across a complex Martech and analytics ecosystem. They will serve as the central point of coordination for intake, prioritization, and issue management while providing clear visibility to stakeholders.
Hybrid · Toronto
The Principal Technical Product Manager will own the end-to-end strategy, roadmap, and execution for complex, data-intensive, and AI-driven product lines. They will act as the primary point of contact for Fortune 500 clients, translating business needs into technical requirements while leading cross-functional teams across different time zones.
Hybrid · Toronto
Own the end-to-end roadmap and delivery of data and AI product lines by translating ambiguous business problems into actionable product requirements. Partner closely with engineering and data science teams to drive product launches while managing stakeholder expectations and success metrics.
Hybrid · Toronto
Lead the architecture, design, and delivery of enterprise-scale data platforms while partnering with Fortune 500 clients to define technical strategy. You will mentor engineering teams, establish best practices, and ensure high-quality production deployment of scalable data products.
Hybrid · Toronto
Design, build, and operate cloud infrastructure and CI/CD pipelines while ensuring system reliability and performance. Lead the technical direction for DevOps, mentor engineers, and collaborate with developers to streamline production deployments.
Hybrid · Toronto
Build and improve agent orchestration, multi-agent workflows, and production-ready AI applications using the Continuum platform. Develop tool-calling functionality, retrieval pipelines, and evaluation systems to ensure AI safety and performance.
Hybrid · Toronto
Own the end-to-end lifecycle and strategy for a portfolio of analytical data products to drive business value for clients. Collaborate with engineering and architecture teams to deliver scalable solutions while serving as the primary point of contact for stakeholders.
Hybrid · Toronto
The role focuses on automating and optimizing cloud infrastructure to accelerate application deployment, testing, and release. Responsibilities include monitoring performance, managing scalability, and partnering with developers to ensure high availability across environments.
Hybrid · Toronto
Design, develop, and debug full-stack software applications while collaborating with senior developers to maintain architectural standards. The role involves working with LLM-based technologies and participating in agile development cycles to create innovative user experiences.
Hybrid · Toronto
The role involves building and integrating AI-powered features and LLM APIs into backend applications and workflows. You will develop scalable backend services, maintain APIs, and collaborate with cross-functional teams to translate business requirements into technical solutions.
Hybrid · Toronto
Architect and implement end-to-end AI-powered features, including model integration, prompt engineering, and deployment into production systems. Collaborate with cross-functional teams to build scalable backend infrastructure, APIs, and MLOps workflows that support intelligent automation.
Hybrid · Toronto
The Data Engineer will design, implement, and optimize big data pipelines in Databricks, developing scalable ETL workflows to process large datasets. They will collaborate with cross-functional teams to enable advanced AI/ML workflows and ensure data integrity and quality in all pipelines.
Hybrid · Toronto
The role involves designing and developing scalable, service-based architectures, remaining hands-on in coding, and architecting system integrations across internal services and third-party platforms using various protocols. Responsibilities also include contributing to AI-enabled features, defining API contracts, and enforcing best practices in code quality and testing.
